We built SwiftChat to stop hating our WhatsApp bill.
And to stop missing internal-note threads, losing campaign attribution, and waiting two weeks for an analytics view that doesn't crash.
We'd been running WhatsApp customer engagement for two years on three different BSPs before starting SwiftChat. Every one of them gave us roughly the same product with a different bill.
Specifically: a shared inbox we'd use 8 hours a day; a broadcast composer that got 90% of the way there; a chatbot builder we'd outgrow in month four; an API we could trust; a sales call when we asked about funnels; and an invoice that ran 2-3× our headline plan because Meta charges, agent overflow, and three add-ons stacked.
The thesis behind SwiftChat is small but specific: charge Meta at cost, ship the analytics that actually matter, and treat AI as an operator instead of a feature. The work has been to put that thesis into real code — every screen, every webhook, every billing line.
— The team
Four principles, in writing
Predictable bills.
Meta charges at cost. Add-ons listed on the pricing page. A next-bill forecast in your dashboard 1-2 weeks before the invoice lands.
AI as a co-worker.
Not a chat node. Not a widget. AI agents are operators in your team inbox — assignable, audited, with their own access tokens.
Real reports, real funnels.
CTR per button. Opt-out rate per campaign. A/B testing with statistical significance. Funnels you can build without exporting CSVs.
Built where customers are.
EU, IN, and US data residency, no premium add-on. Stripe-native checkout, plus Razorpay, PayU, and Adyen.
Small. Senior. Building in public.
- Meta · WhatsApp Business Solution Provider
- Stripe Verified Partner
- Shopify Plus Tech Partner
- AWS Activate